Activity based electrical computer system request processing architecture

ABSTRACT

An electrical computer system processing architecture for providing an indication of activity in the electrical computer system, the electrical computer system processing architecture comprising a plurality of client computers connected to at least one server by a computer network. Each of the client computers is configured to provide requests to the at least one server. The or each server comprises a store for storing requests provided by the plurality of client computers. The or each server is configured to match complementary requests from the plurality of client computers stored in the store. Following the matching of complementary requests, the or each server counts unmatched requests corresponding to one or other of the complementary requests in the store, and outputs the counted number of unmatched requests to provide the indication of activity in the computer system.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.17/244,363, filed Apr. 29, 2021 entitled “Activity Based ElectricalComputer System Request Processing Architecture,” now U.S. Pat. No.11,310,168, which is a continuation of U.S. application Ser. No.16/588,036, filed Sep. 30, 2019 entitled “Activity Based ElectricalComputer System Request Processing Architecture,” now U.S. Pat. No.11,025,562, which is a continuation of U.S. application Ser. No.15/450,428, filed Mar. 6, 2017 entitled “Activity Based ElectricalComputer System Request Processing Architecture,” now U.S. Pat. No.10,469,409, which claims the benefit of U.S. Patent Application No.62/304,415, entitled “Electrical Computer System ProcessingArchitecture”, filed Mar. 7, 2016 and U.S. Patent Application No.62/304,505, entitled “Electrical Computer System ProcessingArchitecture”, filed Mar. 7, 2016, all of which are incorporated hereinby reference in their entirety and relied upon.

FIELD OF THE INVENTION

The present invention relates to an electrical computer systemprocessing architecture and, in particular, an electrical computersystem processing architecture that provides an indication of activityin the electrical computer system.

BACKGROUND OF THE INVENTION

Today's computer systems typically include many different computers suchas servers and general purpose personal computers (such as, desktop andlaptop computers) acting as clients that are connected to the servers ona computer network. The servers provide resources to the clients. Aserver of this distributed architecture can provide resources toclients, on each client's request, around the world and therefore indifferent time zones. As clients for a server may be in different timezones, users can be expected to request resources from servers atvarying times particularly as the working day varies across the globe.

BRIEF SUMMARY OF THE INVENTION

Embodiments of the present invention solve the technical problem ofproviding an accurate indication of activity in the computer system and,in particular, in a complex computer system involving many clientcomputers connected to a server on a computer network.

The invention in its various aspects is defined in the independentclaims below to which reference should now be made. Advantageousfeatures are set forth in the dependent claims.

Arrangements are described in more detail below and take the form of anelectrical computer system processing architecture for providing anindication of activity in the electrical computer system, the electricalcomputer system processing architecture comprising a plurality of clientcomputers connected to at least one server by a computer network. Eachof the client computers is configured to provide requests to the atleast one server. The or each server comprises a store for storingrequests provided by the plurality of client computers. The or eachserver is configured to match complementary requests from the pluralityof client computers stored in the store. Following the matching ofcomplementary requests, the or each server counts unmatched requestscorresponding to one or other of the complementary requests in thestore, and outputs the counted number of unmatched requests to providethe indication of activity in the computer system.

Example arrangements are simple and computationally efficient yetaccurate.

In an aspect of the present invention, there is provided an electricalcomputer system processing architecture for providing an indication ofactivity in the electrical computer system, the electrical computersystem processing architecture comprising: a plurality of clientcomputers being connected to at least one server by a computer network;each of the client computers being configured to provide requests to theat least one server; the or each server comprising a store for storingrequests provided by the plurality of client computers, the or eachserver being configured to: match complementary requests from theplurality of client computers stored in the store, following matching ofcomplementary requests, count unmatched requests corresponding to one orother of the complementary requests in the store, and output the countednumber of unmatched requests to provide the indication of activity inthe computer system.

In another aspect of the present invention, there is provided a serverforming part of an electrical computer system processing architecture,the server for providing an indication of activity in the computersystem, the server comprising: a store for storing requests provided bya plurality of client computers, and the server being configured to:match complementary requests from the plurality of client computersstored in the store, following matching of complementary requests, countunmatched requests corresponding to one or other of the complementaryrequests in the store, and output the counted number of unmatchedrequests to provide the indication of activity in the computer system.

In another aspect of the present invention, there is provided acomputerized method for providing an indication of activity in acomputer system, the computerized method comprising: a server of thecomputer system receiving requests from a plurality of client computersconnected to the server by a computer network; each of the clientcomputers being configured to provide requests to the at least oneserver; the server storing the requests provided by the plurality ofclient computers; the server matching complementary requests from theplurality of client computers stored in the store; following matching ofcomplementary requests, the server counting unmatched requestscorresponding to one or other of the complementary requests in thestore; and outputting the counted number of unmatched requests toprovide the indication of activity in the computer system.

In a yet further aspect of the present invention, there is provided acomputer readable medium comprising instructions for carrying a methodon a server for providing an indication of activity in a computersystem, the computerized method comprising: receiving requests from aplurality of client computers connected to the server by a computernetwork; each of the client computers being configured to providerequests to the at least one server; the server storing the requestsprovided by the plurality of client computers; the server matchingcomplementary requests from the plurality of client computers stored inthe store; following matching of complementary requests, the servercounting unmatched requests corresponding to one or other of thecomplementary requests in the store; and outputting the counted numberof unmatched requests to provide the indication of activity in thecomputer system.

The requests may be provided in XML format. Complementary requests maybe matched by time priority provided by the plurality of clientcomputers.

One example of a type of computer system where it is very useful to knowthe activity of the computer system is an electronic trading system and,in particular, an anonymous trading computer system. These are highlycomplex computer systems with many components.

The inventors of the present application are the first to appreciatethat activity in an electronic trading system may be linked to a centrallimit order book quote count rather than a deal or trade count. A dealor trade count is where an order or quote has actually been matched. Incontrast, embodiments of the present invention count unmatched quotes ororders in an order book.

Embodiments of the present invention provide the technical advantage ofneutralizing technology advantages of traders. For example, algorithmictraders or computerized traders with quick communications do not have anadvantage.

In examples of the present arrangement, products such as financialproducts are linked (for example, from EBS Brokertec platforms) usingdynamically calculated post trade time intervals, referencing uniqueanonymous and disclosed markets (such as EBS Markets) central limitorder book's (CLOB) quote counts as a reference point. Frequency ofquote update in the CLOB is used. This measurement reflects marketactivity and volatility, which is directly aligned with the risk holdingperiods for electronic trading desks at banks.

The inventors of the present application have appreciated that the timeit takes to receive a predetermined number of orders in a CLOB reflectsthe activity of the market/product in general, better than counting dealtime, price volatility or price update frequencies from aggregated pricemakers. The inventors of the present application have appreciated thatthe reason for this is that the order received is an intention to tradeor, in other words, an invitation to trade. They have appreciated thatan individual price stream from a bank or an aggregated price stream,for example an electronic streaming price (ESP) may vary its pace ofactivity, but its reasonably constant during the day and reflects manyfactors outside the core product's price activity. The inventors haveappreciated that a collection of orders making up a CLOB is a uniqueecosystem and that the time it takes to reach a certain order count isunique to a central limit order book market.

This method described links transactions to the unique activity of theunderlying market at the time of dealing. In slow markets, calculationperiods will be longer and in fast market conditions incurrencies/products like EURUSD, could be as short as a few seconds.

Products use different time periods for each trade thereby making thecalculations much more relevant and reflective of the risk holdingperiods at the banks and other participants.

In an aspect of the present invention, there is provided a computersystem for providing an indication of activity in an electronic tradingsystem, the computer system comprising: a plurality of order inputdevices connected to at least one matching engine by a computer network;each of the order input devices being configured to submit orders to thematching engine; the matching engine being configure to store orders inan order book submitted by the order input devices and to matchcomplementary orders submitted by the order input devices, the matchingengine being configured to: following matching of complementary orders,count unmatched orders corresponding to one or other of thecomplementary orders stored in the order book, and output the countednumber of unmatched orders to provide the indication of activity in thecomputer system.

In another aspect of the present invention, there is provided a matchingengine for providing an indication of activity in an electronic tradingsystem, the matching engine being configured to store orders in an orderbook submitted by order input devices and to match complementary orderssubmitted by the order input devices, the matching engine beingconfigured to: following matching of complementary orders, countunmatched orders corresponding to one or other of the complementaryorders stored in the order book, and output the counted number ofunmatched orders to provide the indication of activity in the computersystem.

In another aspect of the present invention, there is provided a methodof providing an indication of activity in an electronic trading system,the method comprising: a plurality of order input devices submittingorders to at least one matching engine of the electronic trading systemby a computer network; the matching engine storing, in an order book,the orders submitted by the order input devices and matchingcomplementary orders submitted by the order input devices, followingmatching of complementary orders, the matching engine counting unmatchedorders corresponding to one or other of the complementary orders storedin the order book, and outputting the counted number of unmatched ordersto provide the indication of activity in the electronic trading system.

The order book may be a CLOB. The orders may be limit orders. A limitorder is an order to buy or sell at a specified price or better. A limitorder may not be executed if the price set cannot be met during the timeit is open. The orders may be provided in XML format The orders may bematched in price/time priority where the time is the time the orders aresubmitted by an order input device or terminal.

A computer readable medium, such as a CD-ROM, DVD-ROM or USB flashdrive, may be provided comprising instructions for carrying out themethod described above on a computer.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be described in more detail, by way of example, withreference to the accompanying drawings, in which:

FIG. 1 is a schematic view of an electrical computer system processingarchitecture embodying an aspect of the present invention;

FIG. 2 is a flow diagram illustrating the method implemented by theelectrical computer system processing architecture of FIG. 1 ;

FIG. 3 is a timeline illustrating the method implemented by theelectrical computer system processing architecture of FIG. 1 ; and

FIGS. 4 to 6 are graphs illustrating the effectiveness of the electricalcomputer system processing architecture of FIG. 1 .

Like features in the Figures have been given like reference numerals.

DETAILED DESCRIPTION OF THE INVENTION

An electrical computer system processing architecture for providing anindication of activity in the computer system is illustrated in FIG. 1 .The computer system comprises at least one server in the form of anarbitrator computer or matching engine 12 and a plurality of clientcomputers in the form of broker computers or order input devices 18 thatare connected to the at least one server by a computer network.

In this example, the computer system takes the form of an anonymoustrading computer system. These types of computer system are widely usedto trade fungible instruments, particularly financial instruments suchas foreign exchange (FX) products. These systems have been verysuccessful and are used for the majority of transactions in someinstruments, for example spot FX.

As their name suggests, anonymous trading systems do not allow theparticipants to know the identity of potential counterparties to atransaction until the trade has been confirmed. One well known system,the EBS platform, described in U.S. Pat. No. 5,375,055 incorporatedherein by reference requires traders to input quotes in the forms ofbids and offers into the system via their trader terminals. Quotes ororders have a price and an amount or size. These quotes are matched withother quotes in the system by a matching engine or arbitrator. Where amatch is found, a deal will be executed between the parties, once it hasbeen established that each party has sufficient credit with the otherfor the deal. A market distributor is arranged between the arbitratorand a bank node, at which is a credit matrix indicative of creditrelationships assigned by a bank to all counterparties on the system.The market distributor is responsible for constructing a market view foreach trading floor based on their credit as represented by the binarycredit matrix stored at the market distributor. Thus, traders at a giventrading floor are only shown quotes input into the system by partieswith whom they have credit. In this platform, the actual credit limitsare stored at bank nodes.

Once a deal has been concluded, details of the trade, including theidentity of the parties and the price at which the deal was concluded,are distributed to all trading floors. Thus, the system is no longeranonymous once deals have been completed.

In this platform, visible quotes are matched with other quotes in thesystem by the matching engine or arbitrator in price/time priority. Thatis to say, when two or more parties submit an invisible order inresponse to a visible order, quotes with the best price are matchedfirst, if there are two or more quotes at the same price, they arematched in time input into the system priority (the first order receivedis matched).

Increasingly, so called algorithmic or algo traders are traded ontrading systems of this type together with human traders. Algo tradersare programmed computers that react to market conditions to submitorders into the trading system. They can react much quicker than a humantrader and so will generally be able to respond to changes in marketdata and respond more quickly in terms of order entry or cancel thanhuman traders.

The computerized method and computer system is suitable forimplementation on any credit screened electronic, computerized tradingsystem or anonymous trading system for trading fungibles in the form offinancial instruments such as foreign exchange products and, inparticular, spot FX. Various examples exist in the prior art of suchsystems, including that of European patent application publication No.EP0399850 of Reuters Ltd, which discloses a centralized host system inwhich traders communicate via trader workstation computers with a hostcomputer which holds credit, performs order matching and executes deals.U.S. Pat. No. 5,375,055 mentioned above discloses a distributed matchingsystem in which matching takes place at arbitrator computers but actualcredit limits are held at bank node computers through which traderworkstations communicate with the system. A yes/no credit matrix isstored at market distributor computers arranged between the bank nodesand the arbitrators and which are responsible for credit filtering ofquotes on the basis of the credit matrix and for the formation anddistribution of market views to trading floors. A further example isdisclosed in international patent application with publication No.WO01/98960 which describes a distributed system using a network ofbroking node computers in which each broking node computer combinesmatching, market distribution and deal execution functionality. Hybridsystems also exist in which the broking node computer concept isincorporated into the distributed system of U.S. Pat. No. 5,375,055.Such a trading system 10 system is shown in FIG. 1 in which tradingfunctionality is allocated to several progressively distributed tiers.Tiers 1 through 3 reside on the trading system provider network. Tier 4represents the customer's or traders' own trading infrastructure.

Broadly, in this anonymous trading system traders input quotes in theforms of bids and offers into the system via their trader terminals.Quotes have a price and an amount or size. These quotes are matched withother quotes in the system by a matching engine or arbitrator. Where amatch is found, a deal will be executed between the parties, once it hasbeen established that each party has sufficient credit with the otherfor the deal. A hardware component referred to as a broker sits or islocated between the arbitrator and a dealing floor, at which sits or islocated a credit matrix representing the bi-lateral credit relationships(granted and received) of a bank with each counterparty on the system.The broker is responsible for constructing a market view for eachtrading floor (deal code) based on their bi-lateral credit relationshipsas represented by the binary credit matrix stored at the broker. Thus,traders at a given trading floor are only shown quotes input into thesystem by parties with whom they have credit. In this platform, theactual credit limits are stored at the broker.

Once a deal has been concluded, details of the trade, including price,size and counterparty details are exchanged between counterparties tothe trade. Only counterparties to a trade are informed of size andcounterparty name but the rate at which the trade took place will beincluded within a market data feed, in this example, EBS Market Dataincluding paid, given, highs, and lows and this is published more widelyand available to other traders.

In this platform generally, visible quotes are matched with other quotesand/or hits (referred to as buys/sells or IOCs (immediate or cancel)) inthe system by the matching engine or arbitrator. In examples of thepresent invention operating on this platform, in some circumstances,visible quotes are matched with other quotes and/or hits by the matchingengine or arbitrator in price/time priority.

In price/time priority, when two or more parties submit orders in anattempt to match a visible order, quotes with the best visible price arematched first, if there are two or more quotes at the same price, theyare matched in time input into the system priority (the first orderreceived is matched).

In more detail, in the electronic trading system or electrical computersystem processing architecture 10 of FIG. 1 , Tier 1 or the core hoststhe matching engines, or arbitrators 12 each provided as a resource on aserver. These are each a single computer or group of computers on anetwork. In this example, only one arbitrator is shown for simplicity.However, in practice, three arbitrators are used one in each majortrading center of Europe (London), America (New York) and Asia (Tokyo).The arbitrators have a global view of the market, facilitating globalliquidity. This tier also supports centralized transactional persistenceand analysis using log manager 14 and persistent store 16. Again, thisis a computerized process with the functionality being carried out byone or more computers on a network. The arbitrators are constantlysynchronized, so that quotes submitted in a single region are instantlyavailable globally. Thus, servers in each country can expect to seevarying activity throughout the day in which the server is located astrading days in the different countries happen. A peak in activity canbroadly be expected when more than one trading day in the major tradingcenters is happening.

The primary roles of an arbitrator or matching engine 12 are to maintainthe global order book and credit books for its region, propose deals bymatching credit compatible orders and quotes and distribute market datato other arbitrators and downstream computerized components. Inparticular, the matching engine matches maker quotes in an order bookwith takes. The quotes and takes are input by trader input devices asdescribed further below.

Transactions from each arbitrator are synchronously persisted inredundant log files. This guarantees that no transactional data is everlost. Transactional data is also passed in real time to the market datasubsystem (formed of one or more computers on a network) for analysisand archiving.

The arbitrator computer or matching engine 12 communicates with brokersor computerized brokers 18. Each broker is formed of one or morecomputers on a network. Only a single broker is shown in FIG. 1 forsimplicity. In practice, a plurality of brokers are provided. Thebrokers are housed in tier 2 or regional distribution site. The brokersmanage the interaction between the trading workstations or trader inputdevices or clients of tier 3 (described below) and the core of tier 1described above. Each broker represents a group of trading floors onwhich the trader input devices reside to the core. The broker's database20 (run on one or more computers on a network) persists thefloor-specific configuration settings and deal history.

The brokers are electronic agents which represent a trading floor to theelectronic trading system. Trading floor configuration settings,including entitlements, credit limits, and settlement instructions, arepersisted in the broker database. The broker disseminates market viewsand news to its trading floors and manages the lifecycle of orders anddeals for its floors. During trade negotiation, the broker handles thefine-grained credit validation and exchange of settlement instructionsbetween counterparty floors.

A single broker represents a group of trading floors in its geographicalproximity. In this example, brokers are hosted in one of three regionaldistribution sites (London, New York, Tokyo).

Tier 3 or the bank access floor hosts a real time view server (RTV) 22,which is a server that resides locally on a bank floor (in practice, itmay be implemented by one or more computers on a network). It plays animportant role in conserving network traffic and enhancing the speed andscalability of the trading system. As a floor-based server, the RTVperforms all the floor-wide services for the trading entities (both spot(manual or human trader) workstations and spot automated tradingservers) on its floor. These services include data aggregation, caching,and distribution. The RTV is also responsible for the delivery ofcompleted deal information to the deal feed server on its floor. The RTVmay be, for example, deployed as a stand-alone dedicated server orco-hosted on a spot workstation 24 provided in this tier, depending onthe volume of transactions handled.

The spot workstation (or trader input device or client in the form of amanual trader controlled input device) 24 is the trading systemfront-end application that provides spot trading functionality throughan intuitive graphical user interface on a display. This functionalityincludes maker trader input device and taker trader input devicefunctionality. Makers put requests, namely open orders or quotes in theform of bids and offers available to other traders, into the market.Takers hit the orders or quotes put into the market by makers. Thequotes include a quote price and a quote size or amount. The manualtrader controlled input device or client includes price panels as partof its display that displays both the system-wide “best price” and thecredit-screened “dealable best price” for a particular currency. Pricescan be hit by takers directly from the price panel. It also includesquote panels that are used to provide requests or, in other words,submit or input a quote in the form of a bid or offer into the tradingsystem.

This tier also includes a spot automated trading server 26 (another typeof trader input device, that takes the form of one or more computers ona network) that supports automated trading by exposing an XML interfaceto the trading system. This too may act both as a maker trader inputdevice and a taker trader input device. The server is an automatedtrading interface that provides for direct integration between acustomer's trading engine and the trading system, thereby enabling modelor program trading and the maintenance of a 24-hour order book. Fulltrading capability is exposed using the XML interface which can beaccessed directly by the customer's model applications, which mayinclude: mathematical models, arbitrage models, and risk managementmodels. The server is the component that intermediates between thecustomer-provided trader input device 24 in the form of a client and thetrading system. Architecturally, the server is similar to a workstation,except that whereas a workstation intermediates between a graphical userinterface on a display and trading messages, the server translates fromXML messaging protocol to the trading messages. Also similar to aworkstation, the server performs the tasks of user authentication andinput validation. XML messages are validated both for conformance to theXML protocol and for compliance with trading system dealing rules.

This tier also hosts a computerized deal feed system 28 (in the form ofone or more computers on a network) that provides a feed of completeddeal information for straight through processing (STP); it automates thedelivery of post-deal information including delivering completed dealtickets to a deal feed database 30 run on one or more computers.

Finally, tier 4 on the customer site on the customer network, includesprocesses outside the trading system provider firewall, including, inthis example, customer STP processors 32 (provided by one or morecomputers on a network) and an automated trading client 34 (provided byone or more computers on a network).

The automated trading client or Ai client 34 is any customer managedapplication that communicates with the Ai server through the tradingsystem XML protocol. The clients may be written in, for example, Java,C++, Microsoft Excel, or any language that can create XML messagesconforming to the trading system protocol.

Embodiments of the present invention are not limited to any particulararchitecture and may be implemented on the system described above and onother systems. While XML is described as an example of the messagingprotocol used, other messaging protocols could be used.

The servers in the form of matching engines or arbitrators 12 ofembodiments of the present invention maintain the order book.

Broadly, the server forms a central limit order book (CLOB) quote countproduct model (CLOB QC) that creates and utilizes dynamically calculatedpost trade time intervals based on a count of unique quotes entered intothe CLOB. This measurement reflects market activity and volatility whichis directly aligned with the risk holding periods for electronic tradingdesks at banks. In turn, these dynamic time intervals are used by otherproducts of the trading system (such as EBS Brokertec products) to markto market the value of trades a predetermined time (generally, of theorder of seconds) after conception. Such a CLOB quote count model isavailable to the owner of a CLOB only. Mark to market reflects thecurrent market value.

Referring to FIGS. 1 and 2 , for order or request matching, client floorcodes are assigned to new Ai instances or servers 26 that will in turnbe connected to Broker 18. Ai Clients 34 submit standard good 'tilcancelled (GTC) orders, which may be complementary orders or requestssuch as buy 100 or sell 102 orders to the Ai instance. Preferably,clients submit zero prices for transparency. However, any prices appliedare ignored on both the buy 104 and sell 106 side. All orders aresubjected to configurable minimum quote life (MQL) by pair, with a day 1setting of 3 seconds. Orders are matched by time priority. Once twoorders are matched 108, they are subjected to the credit matrix checksdescribed above.

The match price is derived from a blend of a mid-price from a marketwith anonymous prices (such as EBS Market) and a mid-price from a marketwith disclosed prices (such as EBS Direct). The weighting between themid-prices from the two sources is configured at a per currency pairlevel. In other words, order book prices are retrieved from an anonymousmarket 110 and from a disclosed market 112 and a mid-price is calculatedfrom each of these 114,116 and then blended 118 to produce a mid-rate120. This mid-rate is assigned as a trade price 122.

Once a match occurs, a count is initiated 124 of all unique quotes inthe order book of the matching engine for the respective currency pairof the match (this is described in more detail below with reference toFIG. 3 ) over a predetermined period of time. At the end of the count,when all relevant quotes have been counted 126, a mark to market (MtM)price is then derived. The MtM price is derived by retrieving order bookprices from both the market with anonymous prices (such as EBS Market)128 and the market with disclosed prices (such as EBS Direct) 130,deriving the mid-price of each of these markets 132,134 and thenblending them together 136 in the same way that the match pricedescribed above is derived. This blended rate forms a mid-rate 138 ofthe counted quotes and it is this that forms the MtM price 140completing the process 142.

The count is configurable per currency pair.

As mentioned above, the timeline 200 of FIG. 3 illustrates the countinitiated at step 124 of FIG. 2 of all unique quotes in the order bookof the matching engine for the respective currency pair of the match.Once the initial match has occurred (the so-called hedge trade), pricesof quotes 202, 204, 206, 208 received at the matching engine or serverof the currency pair of interest over a predetermined time period of xseconds after the initial match are combined (where x is a number).These form the mid-prices that form the MtM price 140 described above.

The graph 300 of FIG. 4 illustrates how these time intervals forcurrency pair EURUSD (Euro to United States dollar) change over thecourse of a 20 hour trading period (from 20:00-24:00 GMT the marketsbecome very thin and illiquid and are not calculated here). InLondon/New York cross over (between 12:00-17:00 GMT) when both marketsare open, the average time period to reach an order count of 60 takes5.4 seconds and the range is between 1.5 seconds and 8.2 seconds. Theaverage for the trading day 00:00 GMT to 20:00 GMT is 19.6 seconds andthe average range is 1.5 seconds to 50 seconds. The graph of FIG. 4illustrates that time periods for quote activity vary throughout thecourse of the trading day.

The graph 300 of FIG. 4 illustrates EBS Markets (a combination ofanonymous and disclosed markets) CLOB quote count as a percentile boxplot. In this plot, 50% of the time is within each box 302 (only some ofthe boxes have been given reference numerals for clarity) and whiskers304 show the 5th and 85th percentiles (only some of the whiskers havebeen given reference numerals for clarity). The quote count is plottedin seconds per 60 orders and the medians are plotted as boxes 306 (onlysome of the boxes have been given reference numerals for clarity).

The graph 300 of FIG. 4 illustrates that when data is released at 12.30,the underlying market moves up 1.25% in minutes, from 1.1160 to 1.1300.The CLOB quote count drops from an average time to 60 orders of 20seconds the hour before to only an average of 1.5 seconds in thefollowing hour.

The graph 400 of FIG. 5 illustrates the quantity in Millions EUR for 10levels of the EBS Markets (a combination of anonymous and disclosedmarkets) CLOB (ask quotes are at the top, bid quotes are at the bottom,plotted on the left hand axis in millions) 402 and the EBS Markets CLOBEURUSD mid-rate (in white, plotted on right hand side in Percent Perannum price volatility) 404.

The graph 500 of FIG. 6 is a simple plot of the CLOB quote count versusa standard deviation average of the asset price (502, dark line on graphwith scale on the right hand side). The graph of FIG. 6 shows EBSMarkets (a combination of anonymous and disclosed markets) CLOB quotecount as a percentile box plot with 50% of time within each box 504(only some of the boxes have been given reference numerals for clarity),whiskers 506 showing 5th and 85th percentiles (only some of the whiskershave been given reference numerals for clarity) plotted in seconds per60 orders and the time scale is in seconds on left hand axis; and astandard deviation of the EBS Markets CLOB EURUSD mid-rate (502, darkline plotted on right hand side in percent per annum price volatility).

The graph 500 of FIG. 6 shows how the CLOB quote count is higher whenvolatility is low and vice versa. However, the CLOB quote count is moreresponsive and introduces a lower average time period pre or before themidday data release compared to the standard deviation. When the pricemoves, the CLOB quote count responds immediately to a lower time periodcompared to a standard deviation model.

Embodiments of the present invention have been described. It will beappreciated that variations and modifications may be made to thedescribed embodiments within the scope of the present invention.

The invention claimed is:
 1. A system comprising: a plurality of clientcomputers coupled with a server by a computer network via which each ofthe client computers is configured to provide requests thereto; theserver comprising a memory for storing requests received from theplurality of client computers which have not yet been matched with acomplementary request, the server being configured to: match a requestreceived from one of the plurality of client computers with one or moreof the stored requests complementary thereto and, based thereon, removethe one or more stored requests from the memory; count, during a timeinterval subsequent to the match, unmatched requests received from theplurality of client computers which are complementary to the removed oneor more stored requests; and output the counted number of unmatchedrequests as an indication of activity in the system.
 2. The system ofclaim 1, wherein the server is one of a plurality of servers, eachlocated in a different geographic region.
 3. The system of claim 2,wherein each of the plurality of servers is coupled with a differentplurality of client computers.
 4. The system of claim 2, wherein each ofthe plurality of servers synchronizes the requests stored in the memorythereof with requests stored in the memories of the others of theplurality of servers.
 5. The system of claim 1, wherein each of theplurality of client computers is located in a different geographicregion.
 6. The system of claim 1, wherein the server is furtherconfigured to store, in the memory, received requests for which nostored requests are complementary thereto.
 7. The system of claim 1,wherein each of the requests comprise orders to trade one or morefinancial instruments.
 8. The system of claim 1, wherein the servercomprises a matching engine.
 9. The system of claim 1, wherein thestored requests comprise a central limit order book.
 10. The system ofclaim 1, wherein the requests are provided in XML format.
 11. The systemof claim 1, wherein stored requests are matched with a received requestby price and time priority.
 12. The system of claim 1, wherein the timeinterval is different for different received requests.
 13. The system ofclaim 1, wherein the time interval is defined based on a delay between aclient computer of the plurality of client computers learning of arequest being stored in the memory to learning that the stored requesthas been removed from the memory.
 14. The system of claim 1, wherein thetime interval is dynamically defined based on a count of unique requestsreceived by the server.
 15. The system of claim 1, wherein the server isfurther configured to execute another transaction at a value computedbased on the counted number of unmatched requests.
 16. The system ofclaim 1, wherein the counted number of unmatched requests is anindication of volatility.
 17. A computer implemented method comprising:receiving, by a server, a request from one of a plurality of clientcomputers coupled with a server by a computer network via which each ofthe client computers is configured to provide requests thereto, theserver comprising a memory for storing requests received from theplurality of client computers which have not yet been matched with acomplementary request; matching, by the server, the received requestwith one or more of the stored requests complementary thereto and, basedthereon, removing the one or more stored requests from the memory;counting, by the server during a time interval subsequent to thematching, unmatched requests received from the plurality of clientcomputers which are complementary to the removed one or more storedrequests; and outputting, by the server, the counted number of unmatchedrequests as an indication of activity.
 18. The computer implementedmethod of claim 17, wherein the server is one of a plurality of servers,each located in a different geographic region.
 19. The computerimplemented method of claim 18, wherein each of the plurality of serversis coupled with a different plurality of client computers.
 20. Thecomputer implemented method of claim 18, further comprisingsynchronizing, by each of the plurality of servers, the requests storedin the memory thereof with requests stored in the memories of the othersof the plurality of servers.
 21. The computer implemented method ofclaim 17, wherein each of the plurality of client computers is locatedin a different geographic region.
 22. The computer implemented method ofclaim 17, further comprising storing, by the server in the memory,received requests for which no stored requests are complementarythereto.
 23. The computer implemented method of claim 17, wherein eachof the requests comprise orders to trade one or more financialinstruments.
 24. The computer implemented method of claim 17, whereinthe server comprises a matching engine.
 25. The computer implementedmethod of claim 17, wherein the stored requests comprise a central limitorder book.
 26. The computer implemented method of claim 17, wherein therequests are provided in XML format.
 27. The computer implemented methodof claim 17, wherein stored requests are matched with a received requestby price and time priority.
 28. The computer implemented method of claim17, wherein the time interval is different for different receivedrequests.
 29. The computer implemented method of claim 17, wherein thetime interval is defined based on a delay between a client computer ofthe plurality of client computers learning of a request being stored inthe memory to learning that the stored request has been removed from thememory.
 30. The computer implemented method of claim 17, wherein thetime interval is dynamically defined based on a count of unique requestsreceived by the server.
 31. The computer implemented method of claim 17,further comprising executing, by the server, another transaction at avalue computed based on the counted number of unmatched requests. 32.The computer implemented method of claim 17, wherein the counted numberof unmatched requests is an indication of volatility.
 33. An apparatuscomprising: a memory for storing requests received from a plurality ofclient computers via a computer network which have not yet been matchedwith a complementary request; and the apparatus being configured to:match a request received from one of the plurality of client computerswith one or more of the stored requests complementary thereto and, basedthereon, remove the one or more stored requests from the memory; count,during a time interval subsequent to the match, unmatched requestsreceived from the plurality of client computers which are complementaryto the removed one or more stored requests; and output the countednumber of unmatched requests as an indication of activity in the system.34. A non-transitory computer readable medium comprising instructionsexecutable by a processor which, when executed by the processor, causethe processor to: receive a request from one of a plurality of clientcomputers via a computer network via which each of the client computersis configured to provide requests thereto; store, in a memory, requestsreceived from the plurality of client computers which have not yet beenmatched with a complementary request; match the received request withone or more of the stored requests complementary thereto and, basedthereon, remove the one or more stored requests from the memory; count,during a time interval subsequent to the match, unmatched requestsreceived from the plurality of client computers which are complementaryto the removed one or more stored requests; and output the countednumber of unmatched requests as an indication of activity.